CN116252783A

CN116252783A - Collision indication based on yaw rate and lateral speed thresholds

Info

Publication number: CN116252783A
Application number: CN202211582293.XA
Authority: CN
Inventors: 杨明达
Original assignee: Delphi Technologies Inc
Current assignee: Anbofu Technology Co ltd
Priority date: 2021-12-10
Filing date: 2022-12-09
Publication date: 2023-06-13
Also published as: US12145581B2; EP4194297A1; EP4194297B1; US20230182724A1

Abstract

The techniques and systems herein enable collision indication based on yaw rate and lateral speed thresholds. Specifically, an in-path band is determined for the predicted path of the host vehicle. In response to determining that the target is in-path, lateral movement of the host vehicle at a time is estimated based on whether the yaw rate of the host vehicle meets a yaw rate threshold. The lateral movement of the target at that moment is also determined based on whether the lateral velocity of the target meets a lateral velocity threshold. The collision indication is generated in response to determining that the primary vehicle and the target are likely to be in-band at the time based on the lateral movement. In this way, the collision indication more accurately reflects an impending collision, thereby improving safety while also reducing false positive events.

Description

Collision indication based on yaw rate and lateral speed thresholds

Background

Determining whether a collision with a target object is imminent is important for many vehicle operations (e.g., advanced Driver Assistance System (ADAS), automatic Emergency Braking (AEB), enhanced Steering Assistance (ESA), semi-autonomous driving techniques, autonomous driving techniques). For example, the AEB system may apply a braking force when an impending collision is determined, or the ESA system may provide steering inputs to avoid the collision. Accurately determining an impending collision not only mitigates actual threats (e.g., those that may lead to a collision), but also minimizes false positives (e.g., those that do not lead to a collision). In some cases, conventional techniques fail to accurately determine an impending collision. Thus, downstream operations (e.g., ADAS, AEB, ESA) are negatively impacted, which may result in reduced security and/or user experience.

Disclosure of Invention

This document relates to systems, assemblies, techniques, and methods for implementing collision indication based on yaw rate and lateral speed thresholds. The techniques and methods described herein may be performed by systems and/or components. The systems and components include means (e.g., a processing system) for performing the techniques and methods described herein.

Some aspects described below include a method comprising: the predicted path and the in-path band of the predicted path of the host vehicle are determined. The method further comprises the steps of: determining whether the target is in-band within the path; and in response to determining that the target is in-band within the path: determining a primary lateral movement based on whether a yaw rate of the primary vehicle meets a yaw rate threshold; and determining whether the primary vehicle is likely to be within the in-path band at a future time based on the primary lateral movement and the in-path band. The method further comprises the steps of: determining a target lateral movement based on whether a lateral speed of the target meets a lateral speed threshold; and determining whether the target is likely to be within the in-path band at a future time based on the target lateral movement and the in-path band. The method further comprises the steps of: in response to determining that the host vehicle and the target are likely to be in-band within the path at the future time, a collision indication is generated that causes the host vehicle to perform an action. Other aspects described below include a system for performing the above-described method and a computer-readable storage medium comprising instructions that, when executed by at least one processor, cause the processor to perform the above-described method.

This summary introduces a simplified concept for implementing collision indication based on yaw rate and lateral speed thresholds, which is further described in the detailed description and drawings. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used to determine the scope of the claimed subject matter.

Drawings

Systems and techniques for implementing collision indication based on yaw rate and lateral speed thresholds are described with reference to the following figures, which use some of the same reference numerals throughout to refer to examples of similar or analogous features and components.

FIG. 1 illustrates an example environment in which collision indication based on yaw rate and lateral speed thresholds may be used in accordance with the techniques of this disclosure.

FIG. 2 illustrates other aspects of the example environment of FIG. 1, in accordance with the techniques of this disclosure.

FIG. 3 illustrates an example system of a host vehicle configured to enable collision indication based on yaw rate and lateral speed thresholds in accordance with the techniques of this disclosure.

FIG. 4 illustrates an example data flow for collision indication based on yaw rate and lateral speed thresholds in accordance with the techniques of this disclosure.

FIG. 5 illustrates an example method of collision indication based on yaw rate and lateral speed thresholds in accordance with the techniques of this disclosure.

Detailed Description

SUMMARY

Accurately determining an impending collision with a target is an important tool in many vehicle operations. Various conditions often lead to inaccurate conventional collision determinations. For example, some techniques rely solely on yaw rate of the host vehicle or input from multiple sensors to determine an impending collision with the target. Such techniques are often unreliable (e.g., they may produce too many false positive collision determinations), or too slow to allow enough time for proper reaction of downstream operations when determining an impending collision.

Techniques and systems herein enable collision indication using in-path bands (in-band) in conjunction with lateral movement estimation based on yaw rate and lateral speed thresholds. Specifically, an in-path band is determined for a predicted path of a vehicle. In response to determining that the target is in-path, lateral movement of the host vehicle at a time is estimated based on whether the yaw rate of the host vehicle meets a yaw rate threshold. The lateral movement of the target at that moment is also estimated based on whether the lateral velocity of the target meets a lateral velocity threshold. In response to determining that the primary vehicle and the target are likely to be in-path at the time based on the lateral movement, a collision indication is generated. By determining lateral movement based on whether a threshold is met, the collision indication more accurately reflects an impending collision, thereby improving safety while also reducing false positive events. In this way, downstream operation (e.g., ADAS, AEB, ESA) security and user experience are improved.

Example Environment

FIG. 1 illustrates an example environment 100 in which collision indication based on yaw rate and lateral speed thresholds may be used. The example environment 100 includes a host vehicle 102 and a target 104. The host vehicle 102 may be any type of system (e.g., an automobile, a car, a truck, a motorcycle, an electric bicycle, a boat, an air vehicle). The target 104 may be any type of moving or stationary object (e.g., an automobile, a car, a truck, a motorcycle, an electric bicycle, a boat, a pedestrian, a cyclist, a boulder). The host vehicle 102 may detect the target 104 using one or more sensor systems (e.g., radar sensor, vision sensor, lidar sensor).

The primary vehicle 102 is traveling along the path 106 (e.g., predicted path) at a primary speed 108 and a primary yaw rate 110. As shown, path 106 is curved with radius 112. The primary yaw rate 110 and the primary speed 108 may be used to predict or otherwise determine the path 106 and/or the radius 112. It should be noted that the path 106 may be straight or any other shape without departing from the scope of the present disclosure.

The collision module 114 of the host vehicle 102 (which is at least partially implemented in hardware) includes a path module 116 that determines an in-path band 118. The in-path belt 118 is a transverse belt that is centered on the path 106 and decreases in width along the path 106 away from the primary vehicle 102. The amount of decrease in width of the in-path band 118 may depend on the situation and may be based on the main speed 108, the main yaw rate 110, and/or the distance 120 from the main vehicle 102.

The path module 116 (or more generally, the collision module 114) may determine that the target 104 is within the in-path zone 118, which causes the collision module 114 to determine whether the host vehicle 102 and the target 104 are likely to be within the in-path zone 118 at some future time, as discussed further below.

Fig. 2 illustrates further aspects of the example environment 100. The target 104 has a target lateral velocity 202. The target lateral velocity 202 may be a lateral component of the total velocity (not shown) of the target 104. The collision module 114 also includes a lateral movement module 204, the lateral movement module 204 being configured to determine a primary lateral movement 206 and a target lateral movement 208 in response to determining that the target 104 is within the in-path zone 118. The primary lateral movement 206 indicates how far the primary vehicle 102 may have traveled laterally within a period of time. The time may be based on a Time To Collision (TTC) with the target 104. The target lateral movement 208 indicates how far the primary target 104 may have traveled laterally in the time period.

The collision module 114 is configured to determine whether the primary vehicle 102 and the target 104 are likely to be within the in-path zone 122 after the period of time. If they are likely to be within the in-path zone 122, it may be determined that a collision with the target 104 is imminent (affected by optional other factors, as discussed below).

Example System

FIG. 3 illustrates an example system 300 configured to be disposed in the host vehicle 102 and configured to enable collision indication based on yaw rate and lateral speed thresholds. The components (and sub-components) of the example system 300 may be disposed anywhere within the host vehicle 102 or on the host vehicle 102. The example system 300 may include at least one processor 302, a computer-readable storage medium 304 (e.g., medium, media, multiple media), and a vehicle component 310. These components are operatively and/or communicatively coupled via link 306.

The processor 302 (e.g., application processor, microprocessor, digital Signal Processor (DSP), controller) is coupled to the computer-readable storage medium 304 via link 306 and executes instructions (e.g., code) stored within the computer-readable storage medium 304 (e.g., non-transitory storage devices such as hard drives, SSDs, flash memory, read Only Memory (ROM)) to implement or otherwise cause the collision module 114 (or a portion thereof) to perform the techniques described herein. Although shown within computer-readable storage medium 304, collision module 114 (or a portion thereof) can be a stand-alone component (e.g., having a dedicated computer-readable storage medium that includes instructions and/or is executed on dedicated hardware, such as a dedicated processor, a preprogrammed Field Programmable Gate Array (FPGA), a system on a chip (SOC), etc.). The processor 302 and the computer-readable storage medium 304 may be any number of components, including components distributed throughout the host vehicle 102, remote from the host vehicle 102, dedicated to, or shared with other components, modules, or systems of the host vehicle 102, and/or configured differently than shown without departing from the scope of the present disclosure.

The computer-readable storage medium 304 also contains sensor data 308 generated by one or more sensors (not shown), which may be located locally to the example system 300 or remotely from the example system 300. The sensor data 308 indicates or otherwise enables determination of information that may be used to perform the techniques described herein. For example, the sensor data 308 may indicate or otherwise be used to determine the path 106, the main speed 108, the main yaw rate 110, the radius 112, the distance 120, or the target lateral speed 202.

In some implementations, the sensor data 308 may come from a remote source (e.g., via link 306). The example system 300 may include a communication system (not shown) that receives sensor data from the target 104 or another remote source. For example, a vehicle-to-vehicle or vehicle-to-outside (V2V/V2X) connection may be used to obtain information that may be used to perform the techniques described herein.

The vehicle component 310 includes one or more systems or components communicatively coupled to the collision module 114 and configured to perform a function using an output (e.g., a collision indication) from the collision module 114. The vehicle components 310 may affect the respective dynamics (e.g., speed, acceleration, heading, vehicle configuration, vehicle operation, or function) of the host vehicle 102. For example, the vehicle assembly 310 may include an AEB system that applies a braking force or an ESA system that applies a steering force to mitigate an impending collision. The vehicle component 310 is communicatively coupled to the collision module 114 via the link 306. Although shown as a separate component, the vehicle component 310 may be part of the collision module 114 and vice versa.

By using the example system 300, the host vehicle 102 may more accurately determine impending collisions (e.g., more true positives and fewer false positives) to better utilize downstream operations (e.g., the vehicle components 310). In doing so, the host vehicle 102 may provide better safety and/or experience for occupants of the host vehicle 102, the target 104, and/or other vehicles or pedestrians.

Example data flow

FIG. 4 illustrates an example data flow 400 for collision indication based on yaw rate and lateral speed thresholds. The example data flow 400 may be implemented in any of the previously described environments and by any of the previously described systems or components. For example, the example data flow 400 may be implemented in the example environment 100 and/or by the example system 300. The example data flow 400 may also be implemented in other environments by other systems or components and with other data flows or techniques. The example data flow 400 may be implemented by one or more entities (e.g., the collision module 114). The order in which operations are illustrated and/or described is not intended to be construed as a limitation, and the order may be rearranged without departing from the scope of the present disclosure. Further, any number of operations may be combined with any other number of operations to implement an example data stream or an alternative data stream.

The example data flow 400 begins with an attribute 402 of an environment (e.g., the example environment 100) obtained by the collision module 114. As shown, the attributes 402 include the main speed 108, the main yaw rate 110, road information 404 (e.g., map data, radar positioning data, surrounding objects), a target location 406 (e.g., relative to the main vehicle 102), and the target lateral speed 202.

The attributes 402 may be acquired, received, or determined by the collision module 114 in any manner known to those of ordinary skill in the art. For example, the collision module 114 may determine the attribute 402 directly from the sensor data 308, from a bus or interface connected to a sensor interfacing with the example system 300, or from another module or system of the example system 300. Regardless of how or where the attributes 402 are collected, received, derived, or calculated, the collision module 114 is configured to use the attributes 402 to determine the collision indication 408.

Further to the example data flow 400, attributes 402 are input into the path module 116. The path module 116 is configured to determine the path 106 and the intra-path band 118. Path 106 may be based on a main speed 108 and a main yaw rate 110 and include a radius 112. As discussed above, the in-path band 118 may decrease in width along the path 106 away from the host vehicle 102. The decrease amount may be based on the main speed 108, the main yaw rate 110, and the distance 120 (determined from the target position 406).

The attributes 402 are also entered into the lateral movement module 204. The lateral movement module 204 is configured to determine a primary lateral movement 206 and a target lateral movement 208. To do so, the lateral movement module 204 calculates a yaw rate threshold 410 of the host vehicle 102. Yaw rate threshold 410 may be based on main speed 108, driver input (e.g., main yaw rate 110), and/or road information 404. Yaw rate threshold 410 represents a minimum yaw rate for estimating main lateral movement 206. For example, the primary lateral movement 206 may be determined according to equation 1.

Where ω is the main yaw rate 110, ω _min Is yaw rate threshold 410, R is radius 112, and Δt is time (e.g., TTC with target 104).

The lateral movement module 204 also calculates a lateral velocity threshold 412 for the target 104. The lateral speed threshold 412 may be based on the speed of the target (e.g., the target lateral speed 202), the distance 120, and/or the road information 404. The lateral velocity threshold 412 represents the minimum target lateral velocity 202 used to estimate the target lateral movement 208. For example, the target lateral movement 208 may be determined according to equation 2.

Wherein v is _lat Is the target lateral velocity 202, v _{lat_min} Is a lateral velocity threshold 412.

The primary lateral movement 206, the target lateral movement 208, and the in-path belt 118 are received by a collision determination module 414. The collision determination module 414 is configured to determine whether the primary vehicle 102 and/or the target 104 is likely to be within the in-path zone 118 at that time. To do so, the collision determination module 414 may determine whether the lateral movement (e.g., the primary lateral movement 206 and the target lateral movement 208) is still within the in-path band 118. If so, a collision determination 416 may be made.

The collision determination 416 may be received by a hysteresis module 418, the hysteresis module 418 being configured to determine whether the collision determination 416 should become the collision indication 408. To do so, the hysteresis module 418 may determine whether there are any previous collision determinations 420 for the target 104. In other words, the hysteresis module 418 may generate the collision indication 408 only in response to determining that the target 104 has been a threat (e.g., has had a collision determination 416) for a certain amount of time. Doing so mitigates false positives that may be generated based on transient spikes of the attribute 402 (e.g., due to transient conditions or measurement noise or interference from the sensor).

In lieu of the previous crash determination 420, or in combination with the previous crash determination 420, the hysteresis module 418 may check to see if any bypass conditions 422 are met. The bypass condition 422 may include determining that the target is outside of the road on which the host vehicle 102 is traveling (e.g., based on the target location 406 and the road information 404). In other words, the hysteresis module 418 may ensure that the target 104 is within the roadway before the collision indication 408 is generated.

The bypass condition 422 may also include determining that the primary vehicle 102 is traveling straight while the target 104 is turning. Conversely, the bypass condition 422 may also include determining that the primary vehicle 102 is turning when the target 104 is moving straight. In other words, the hysteresis module 418 may ensure that the host vehicle 102 is not traveling straight when the target is turning or that the host vehicle 102 is not turning when the target 104 is moving straight before the collision indication 408 is generated.

Although shown within the collision module 114, the path module 116, the lateral movement module 204, the collision determination module 414, and/or the hysteresis module 418 may be separate from the collision module 114. For example, the path module 116, the lateral movement module 204, the collision determination module 414, or the hysteresis module 418 may be separate components and/or performed via dedicated hardware.

The collision indication 408 is then output for receipt by the vehicle component 310. The vehicle component 310 uses the collision indication 408 to change the function of the host vehicle 102. For example, the vehicle component 310 may cause an alert (visual, audible, and/or tactile), change the steering angle of the host vehicle 102, apply braking forces to the host vehicle 102, or change the operation of the semi-autonomous or autonomous functions of the host vehicle. It should be noted that the vehicle component 310 may represent a plurality of functions or systems that receive the collision indication 408.

Using the techniques described above, the collision indication 408 may be based on decrements in width of the intra-path bands, yaw rate, and lateral speed thresholds that determine how lateral movement is calculated, hysteresis conditions, and/or bypass scenarios are not met. In this way, the collision indication 408 is more accurate in more environments and situations. Thus, more true positives are generated and more false positives are avoided, thereby improving the safety of passengers, targets 104, and/or other people approaching the host vehicle 102.

Example method

FIG. 5 illustrates an example method 500 for collision indication based on yaw rate and lateral speed thresholds. The example method 500 may be implemented by any of the previously described systems or components in any of the previously described environments and with any of the previously described data flows, process flows, or techniques. For example, the example method 500 may be implemented by the example system 300, and/or by following the example data flow 400 in the example environment 100. The example method 500 may also be implemented by other systems or components, and with other data flows, process flows, or techniques, in other environments. The example method 500 may be implemented by one or more entities (e.g., the collision module 114). The order in which operations are illustrated and/or described is not intended to be construed as a limitation, and the order may be rearranged without departing from the scope of the present disclosure. Further, any number of operations may be combined with any other number of operations to implement example process flows or alternative process flows.

At 502, an in-path band of a host vehicle is determined. For example, the path module 116 may determine the in-path band 118 of the primary vehicle 102 based on the path 106, the primary speed 108, the primary yaw rate 110, and/or the distance 120.

At 504, in response to determining that the target is in-path, lateral movement of the host vehicle at a time is determined based on whether the yaw rate of the host vehicle meets a yaw rate threshold. For example, the path module 116 may determine that the target 104 is within the in-path band 118, and the lateral movement module 204 may determine the yaw rate threshold 410 and use it to determine the primary lateral movement 206 at that time (with the TTC of the target 104).

At 506, the lateral movement of the target at that time is determined based on whether the lateral velocity of the target meets a lateral velocity threshold. For example, the lateral movement module 204 may determine the lateral velocity threshold 412 and use it to determine the target lateral movement 208 at that time.

At 508, a collision indication is generated in response to determining that the primary vehicle and the target are likely to be in-band within the path at the time. For example, the collision determination module 414 may generate the collision determination 416 and pass it to the hysteresis module 418 to generate the collision indication 408.

At 510, a collision indication is output for receipt by a vehicle component. For example, the hysteresis module 418 may output the collision indication 408 for receipt by the vehicle component 310 to change the function of the host vehicle 102.

By affecting the collision indication based on the example method 800, a more accurate collision indication may be generated. In so doing, the efficiency of downstream operations (e.g., the vehicle component 310) is improved while ensuring that these operations are not unnecessarily activated (e.g., false positive steering/braking events). Thus, the safety and experience of people (and other objects) in and around the host vehicle 102 may be improved.

Example

Example 1: a method, the method comprising: determining a predicted path of the host vehicle; determining an intra-path band of the predicted path, the intra-path band centered on the predicted path and decreasing in width along the predicted path away from the host vehicle; determining whether the target is in-band within the path; and in response to determining that the target is in-band within the path: determining a yaw rate of the primary vehicle; determining a yaw rate threshold of the host vehicle, the yaw rate threshold being usable to determine how to determine a host lateral movement of the host vehicle; determining a primary lateral movement based on whether a yaw rate of the primary vehicle meets a yaw rate threshold; determining whether the primary vehicle is likely to be in-path based on the primary lateral movement and the in-path; determining a lateral velocity of the target; determining a lateral velocity threshold of the target, the lateral velocity threshold being usable to determine how to determine a target lateral movement of the target; determining a target lateral movement based on whether a lateral speed of the target meets a lateral speed threshold; determining whether the target is likely to be in-path band at a future time based on the target lateral movement and the in-path band; and generating a collision indication in response to determining that the host vehicle and the target are likely to be in-band within the path at the future time; and in response to generating the collision indication, causing the host vehicle to perform an action.

Example 2: the method of example 1, wherein the predicted path is based on a yaw rate of the host vehicle and a speed of the host vehicle.

Example 3: the method of example 1 or 2, wherein the decrease in width of the in-path band is based on at least one of: the speed of the host vehicle, the yaw rate, or the distance between the host vehicle and the target.

Example 4: the method of example 1, 2, or 3, wherein the yaw rate threshold is based on at least one of: speed, yaw rate, or road information of the host vehicle.

Example 5: the method of any preceding example, wherein determining the primary lateral movement comprises: in response to determining that the yaw rate does not meet the yaw rate threshold, determining that the primary lateral movement is zero; or in response to determining that the yaw rate satisfies the yaw rate threshold, determining a primary lateral movement based on the radius of curvature of the predicted path, the yaw rate, and the future time.

Example 6: the method of any preceding example, wherein the future time comprises an estimated time of collision between the host vehicle and the target.

Example 7: the method of any preceding example, wherein the lateral velocity threshold is based on at least one of: speed of the target, distance between the host vehicle and the target, or road information.

Example 8: the method of any preceding example, wherein determining the target lateral movement comprises: in response to determining that the lateral velocity does not meet the lateral velocity threshold, determining that the target lateral movement is zero; or in response to determining that the lateral speed meets a lateral speed threshold, determining a target lateral movement based on a radius of curvature of the predicted path, a yaw rate, and a future time.

Example 9: the method of any preceding example, wherein the collision indication is further generated in response to at least one of: identifying previous determinations that the host vehicle and the target may be in-band within the path at a future time; determining that the target is in a road on which the host vehicle is traveling; determining that the host vehicle is not traveling straight when the target is turning; or to determine that the host vehicle is not changing lanes or turning while the target is traveling straight.

Example 10: a system comprising at least one processor configured to: determining a predicted path of the host vehicle; determining an intra-path band of the predicted path, the intra-path band centered on the predicted path and decreasing in width along the predicted path away from the host vehicle; determining whether the target is in-band within the path; and in response to determining that the target is in-band within the path: determining a yaw rate of the primary vehicle; determining a yaw rate threshold of the host vehicle, the yaw rate threshold being usable to determine how to determine a host lateral movement of the host vehicle; determining a primary lateral movement based on whether a yaw rate of the primary vehicle meets a yaw rate threshold; determining whether the primary vehicle is likely to be in-path based on the primary lateral movement and the in-path; determining a lateral velocity of the target; determining a lateral velocity threshold of the target, the lateral velocity threshold being usable to determine how to determine a target lateral movement of the target; determining a target lateral movement based on whether a lateral speed of the target meets a lateral speed threshold; determining whether the target is likely to be in-path band at a future time based on the target lateral movement and the in-path band; in response to determining that the host vehicle and the target are likely to be in-band within the path at a future time, a collision indication is generated.

Example 11: the system of example 10, wherein the predicted path is based on a yaw rate of the host vehicle and a speed of the host vehicle.

Example 12: the system of example 10 or 11, wherein the decrease in width of the in-path band is based on at least one of: the speed of the host vehicle, the yaw rate, or the distance between the host vehicle and the target.

Example 13: the system of example 10, 11, or 12, wherein the yaw rate threshold is based on at least one of: speed, yaw rate, or road information of the host vehicle.

Example 14: the system of any of examples 10 to 13, wherein determining the primary lateral movement comprises: in response to determining that the yaw rate does not meet the yaw rate threshold, determining that the primary lateral movement is zero; or in response to determining that the yaw rate satisfies the yaw rate threshold, determining a primary lateral movement based on the radius of curvature of the predicted path, the yaw rate, and the future time.

Example 15: the system of any of examples 10 to 14, wherein the future time comprises an estimated time of collision between the host vehicle and the target.

Example 16: the system of any of examples 10 to 15, wherein the lateral velocity threshold is based on at least one of: speed of the target, distance between the host vehicle and the target, or road information.

Example 17: the system of any of examples 10 to 16, wherein determining the target lateral movement comprises: in response to determining that the lateral velocity does not meet the lateral velocity threshold, determining that the target lateral movement is zero; or in response to determining that the lateral speed meets a lateral speed threshold, determining a target lateral movement based on a radius of curvature of the predicted path, a yaw rate, and a future time.

Example 18: the system of any of examples 10 to 17, wherein the collision indication is generated in response to a previous determination identifying that the host vehicle and the target are likely to be in-band within the path at a future time.

Example 19: the system of any of examples 10 to 18, wherein the collision indication is further generated in response to at least one of: determining that the target is in a road on which the host vehicle is traveling; determining that the host vehicle is not traveling straight when the target is turning; or to determine that the host vehicle is not changing lanes or turning while the target is traveling straight.

Example 20: a computer-readable storage medium comprising instructions that, when executed by at least one processor, cause the processor to: determining a predicted path of the host vehicle; determining an intra-path band of the predicted path, the intra-path band centered on the predicted path and decreasing in width along the predicted path away from the host vehicle; determining whether the target is in-band within the path; and in response to determining that the target is in-band within the path: determining a yaw rate of the primary vehicle; determining a yaw rate threshold of the host vehicle, the yaw rate threshold being usable to determine how to determine a host lateral movement of the host vehicle; determining a primary lateral movement based on whether a yaw rate of the primary vehicle meets a yaw rate threshold; determining whether the primary vehicle is likely to be in-path based on the primary lateral movement and the in-path; determining a lateral velocity of the target; determining a lateral velocity threshold of the target, the lateral velocity threshold being usable to determine how to determine a target lateral movement of the target; determining a target lateral movement based on whether a lateral speed of the target meets a lateral speed threshold; determining whether the target is likely to be in-path band at a future time based on the target lateral movement and the in-path band; in response to determining that the host vehicle and the target are likely to be in-band within the path at a future time, a collision indication is generated.

Example 21: a system, the system comprising: a processor configured to perform the method of any of examples 1 to 9.

Example 22: a computer-readable storage medium comprising instructions that, when executed by at least one processor, cause the processor or associated system to perform the method of any of examples 1 to 9.

Example 23: a system comprising means for performing the method of any of examples 1-9.

Example 24: a method performed by the system of any of examples 10 to 19.

Idioms of the knot

While various embodiments of the present disclosure have been described in the foregoing description and shown in the accompanying drawings, it is to be understood that the disclosure is not so limited, but may be practiced in various ways within the scope of the following claims. From the foregoing description, it will be apparent that various modifications may be made without departing from the spirit and scope of the disclosure as defined by the following claims.

The use of "or" and grammatical-related terms, unless the context clearly dictates otherwise, represents a non-exclusive alternative. As used herein, a phrase referring to "at least one of a list of items refers to any combination of such items, including individual members. As an example, "at least one of a, b, or c" is intended to encompass: a. b, c, a-b, a-c, b-c, and a-b-c, as well as any combination having a plurality of identical elements (e.g., a-a-b, a-a-c, a-b-b, a-c-c, b-b-b, b-b-c, c-c, and c-c-c, or any other ordering of a, b, and c).

Claims

1. A method, the method comprising:

determining whether a target is within an in-path band of a predicted path of a host vehicle, the in-path band being centered on the predicted path and decreasing in width along the predicted path away from the host vehicle; and

in response to determining that the target is in-band within the path:

determining a yaw rate threshold of the host vehicle, the yaw rate threshold being usable to determine how to determine a host lateral movement of the host vehicle;

determining the primary lateral movement based on whether a yaw rate of the primary vehicle meets the yaw rate threshold;

determining whether the primary vehicle is likely to be within the in-path zone at a future time based on the primary lateral movement and the in-path zone;

determining a lateral velocity threshold of the target, the lateral velocity threshold being usable to determine how to determine a target lateral movement of the target;

determining the target lateral movement based on whether a lateral speed of the target meets the lateral speed threshold;

determining whether the target is likely to be within the in-path band at the future time based on the target lateral movement and the in-path band; and

in response to determining that the host vehicle and the target are likely to be in-band within the path at the future time, a collision indication is generated that causes the host vehicle to perform an action.

2. The method of claim 1, wherein the predicted path is based on the yaw rate of the host vehicle and a speed of the host vehicle.

3. The method of claim 1, wherein the decrease in width of the in-path band is based on at least one of: the speed of the host vehicle, the yaw rate, or the distance between the host vehicle and the target.

4. The method of claim 1, wherein the yaw rate threshold is based on at least one of: the speed of the host vehicle, the yaw rate, or road information.

5. The method of claim 1, wherein determining the primary lateral movement comprises:

in response to determining that the yaw rate does not meet the yaw rate threshold, determining that the primary lateral movement is zero; or alternatively

In response to determining that the yaw rate meets the yaw rate threshold, the primary lateral movement is determined based on a radius of curvature of the predicted path, the yaw rate, and the future time.

6. The method of claim 1, wherein the future time comprises an estimated time of collision between the host vehicle and the target.

7. The method of claim 1, wherein the lateral velocity threshold is based on at least one of: the speed of the target, the distance between the host vehicle and the target, or road information.

8. The method of claim 1, wherein determining the target lateral movement comprises:

in response to determining that the lateral velocity does not meet the lateral velocity threshold, determining that the target lateral movement is zero; or alternatively

In response to determining that the lateral speed meets the lateral speed threshold, the target lateral movement is determined based on a radius of curvature of the predicted path, the yaw rate, and the future time.

9. The method of claim 1, wherein the collision indication is generated further in response to at least one of:

identifying a previous determination that the host vehicle and the target are likely to be in-band within the path at the future time;

determining that the target is within a road on which the host vehicle is traveling;

determining that the primary vehicle is not traveling straight when the target is turning; or alternatively

It is determined that the host vehicle is not changing lanes or turning when the target is traveling straight.

10. A system comprising at least one processor configured to:

in response to determining that the target is in-band within the path:

in response to determining that the host vehicle and the target are likely to be in-band within the path at the future time, a collision indication is generated.

11. The system of claim 10, wherein the predicted path is based on the yaw rate of the host vehicle and a speed of the host vehicle.

12. The system of claim 10, wherein the in-path band width decrease amount is based on at least one of: the speed of the host vehicle, the yaw rate, or the distance between the host vehicle and the target.

13. The system of claim 10, wherein the yaw rate threshold is based on at least one of: the speed of the host vehicle, the yaw rate, or road information.

14. The system of claim 10, wherein determining the primary lateral movement comprises:

15. The system of claim 10, wherein the future time comprises an estimated time of collision between the host vehicle and the target.

16. The system of claim 10, wherein the lateral velocity threshold is based on at least one of: the speed of the target, the distance between the host vehicle and the target, or road information.

17. The system of claim 10, wherein determining the target lateral movement comprises:

18. The system of claim 10, wherein the collision indication is generated further in response to a previous determination identifying that the host vehicle and the target are likely to be in-band within the path at the future time.

19. The system of claim 10, wherein the collision indication is generated further in response to at least one of:

20. A computer-readable storage medium comprising instructions that, when executed by at least one processor, cause the processor to:

in response to determining that the target is in-band within the path: